Abstract
We first introduce the general linear mixed model and provide a justification for using REML to fit it. Then, for an irrigation example, we present several mixed models of increasing complexity. The initial model corresponds to a typical split-plot analysis. Next, we present covariance structures that directly describe the variability of repeated measures within whole plots. Finally, we combine the above types into more complicated mixed models, and compare them using likelihood-based criteria.
Keywords
Covariance structure, Mixed model, Restricted maximum likelihood
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Wolfinger, Russ; Miles-McDermott, Nancy; and Kendall, Jenny
(1992).
"ANALYZING SPLIT-PLOT ANDREPEATED-MEASURES DESIGNSUSING MIXED MODELS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1405
ANALYZING SPLIT-PLOT ANDREPEATED-MEASURES DESIGNSUSING MIXED MODELS
We first introduce the general linear mixed model and provide a justification for using REML to fit it. Then, for an irrigation example, we present several mixed models of increasing complexity. The initial model corresponds to a typical split-plot analysis. Next, we present covariance structures that directly describe the variability of repeated measures within whole plots. Finally, we combine the above types into more complicated mixed models, and compare them using likelihood-based criteria.
